Paper Citation Record · LEDGER

FLAME: Towards Federated Fine-Tuning Large Language Models Through Adaptive SMoE

As of 8 August 2026, this Paper Citation Record lists 16 of 16 outbound references and 0 inbound Pith citation observations for arXiv:2506.16600.

A citation records a reference. It does not transfer a finding from one paper to another.

pith.paper-citation-record.v1
2506.16600 v2

Coverage vector

measured 16 of 16 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-06T23:43:12.324753Z

measured 16 of 16 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-08T06:32:00.761636+00:00

measured 0 of 0 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links

measured 0 of 1 external citation measurements

A source-named dated measurement, never combined with another source.

Source: cited_works

Reference resolution

16 of 16 outbound references displayed

verified exact0
verified fuzzy0
unresolved16
parse uncertain0
malformed identifier0
metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 0a014456-dca8-4eeb-bca0-e9c72a570349 · outbound

This paper cites GPT-4 Technical Report.

FLAME: Towards Federated Fine-Tuning Large Language Models Through Adaptive SMoE GPT-4 Technical Report

Reference 1

Resolution: unresolved; no resolver link, observed 2026-08-06T23:43:10.394745Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 0c2110db-3637-4971-a364-cf210e0d6294 · outbound

This paper cites Fine-tuning large language models for specialized use cases.

FLAME: Towards Federated Fine-Tuning Large Language Models Through Adaptive SMoE Fine-tuning large language models for specialized use cases

Reference 2

Resolution: unresolved; no resolver link, observed 2026-08-06T23:43:10.484750Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 0436d0c6-75af-4b8c-ba50-f0f6885ff3a3 · outbound

This paper cites Federated fine-tuning of large language models under heterogeneous tasks and client resources.

FLAME: Towards Federated Fine-Tuning Large Language Models Through Adaptive SMoE Federated fine-tuning of large language models under heterogeneous tasks and client resources

Reference 3

Resolution: unresolved; no resolver link, observed 2026-08-06T23:43:10.594752Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 3717be6b-0776-42b3-b5ab-db9df47284fd · outbound

This paper cites FedAdapter: Efficient Federated Learning for Modern NLP.

FLAME: Towards Federated Fine-Tuning Large Language Models Through Adaptive SMoE FedAdapter: Efficient Federated Learning for Modern NLP

Reference 4

Resolution: unresolved; no resolver link, observed 2026-08-06T23:43:10.734745Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 3851ab99-5fcd-43c2-ada6-36ef73274420 · outbound

This paper cites A survey on mixture of experts in large language models.

FLAME: Towards Federated Fine-Tuning Large Language Models Through Adaptive SMoE A survey on mixture of experts in large language models

Reference 5

Resolution: unresolved; no resolver link, observed 2026-08-06T23:43:10.847588Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 9bcdafde-a193-4679-912b-03e61ce98ed1 · outbound

This paper cites Improved training of mixture-of-experts language gans.

FLAME: Towards Federated Fine-Tuning Large Language Models Through Adaptive SMoE Improved training of mixture-of-experts language gans

Reference 6

Resolution: unresolved; no resolver link, observed 2026-08-06T23:43:10.974756Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 22c4735f-05a5-492b-bb01-4ae23bb39f5d · outbound

This paper cites Federated learning of large language models with parameter-efficient prompt tuning and adaptive optimization.

FLAME: Towards Federated Fine-Tuning Large Language Models Through Adaptive SMoE Federated learning of large language models with parameter-efficient prompt tuning and adaptive optimization

Reference 7

Resolution: unresolved; no resolver link, observed 2026-08-06T23:43:11.035546Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 43fbb149-fcc2-4be3-84fd-0106681701d2 · outbound

This paper cites Alpagasus: Training a better alpaca with fewer data.

FLAME: Towards Federated Fine-Tuning Large Language Models Through Adaptive SMoE Alpagasus: Training a better alpaca with fewer data

Reference 8

Resolution: unresolved; no resolver link, observed 2026-08-06T23:43:11.174888Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation ecc81d5d-252c-4c36-856a-e5fbf090c530 · outbound

This paper cites LLaVA-MoLE: Sparse Mixture of LoRA Experts for Mitigating Data Conflicts in Instruction Finetuning MLLMs.

FLAME: Towards Federated Fine-Tuning Large Language Models Through Adaptive SMoE LLaVA-MoLE: Sparse Mixture of LoRA Experts for Mitigating Data Conflicts in Instruction Finetuning MLLMs

Reference 9

Resolution: unresolved; no resolver link, observed 2026-08-06T23:43:11.344752Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 0cfd8835-fe78-445e-a9e5-be536f650d9a · outbound

This paper cites Robust federated finetuning of llms via alternating optimization of lora.

FLAME: Towards Federated Fine-Tuning Large Language Models Through Adaptive SMoE Robust federated finetuning of llms via alternating optimization of lora

Reference 10

Resolution: unresolved; no resolver link, observed 2026-08-06T23:43:11.474749Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation aeefbf24-e315-4ee6-b8a4-9f3c50a0bb63 · outbound

This paper cites Heterogeneous LoRA for federated fine-tuning of on-device foundation models.

FLAME: Towards Federated Fine-Tuning Large Language Models Through Adaptive SMoE Heterogeneous LoRA for federated fine-tuning of on-device foundation models

Reference 11

Resolution: unresolved; no resolver link, observed 2026-08-06T23:43:11.597726Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 5f869d02-ab42-4021-b1ff-ffe482f0cdb7 · outbound

This paper cites Free dolly: Introducing the world’s first truly open instruction-tuned llm, 2023.

FLAME: Towards Federated Fine-Tuning Large Language Models Through Adaptive SMoE Free dolly: Introducing the world’s first truly open instruction-tuned llm, 2023

Reference 12

Resolution: unresolved; no resolver link, observed 2026-08-06T23:43:11.734757Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 37687138-a24b-4f14-96c9-e67fa9c3b59a · outbound

This paper cites Towards next-generation intelligent assistants leveraging llm techniques.

FLAME: Towards Federated Fine-Tuning Large Language Models Through Adaptive SMoE Towards next-generation intelligent assistants leveraging llm techniques

Reference 13

Resolution: unresolved; no resolver link, observed 2026-08-06T23:43:11.894755Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 12f15a85-fa72-43ac-b219-05cfc7fea3fc · outbound

This paper cites Federated Sketching LoRA: A Flexible Framework for Heterogeneous Collaborative Fine-Tuning of LLMs.

FLAME: Towards Federated Fine-Tuning Large Language Models Through Adaptive SMoE Federated Sketching LoRA: A Flexible Framework for Heterogeneous Collaborative Fine-Tuning of LLMs

Reference 14

Resolution: unresolved; no resolver link, observed 2026-08-06T23:43:12.006331Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 463c25d6-b11d-4cee-84fe-f9b38f9a3c7d · outbound

This paper cites Pm-moe: Mixture of experts on private model parameters for personalized federated learning.

FLAME: Towards Federated Fine-Tuning Large Language Models Through Adaptive SMoE Pm-moe: Mixture of experts on private model parameters for personalized federated learning

Reference 15

Resolution: unresolved; no resolver link, observed 2026-08-06T23:43:12.138413Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 58426aa9-67d3-48b5-9f44-d4264f6dac2f · outbound

This paper cites QMoE: Practical Sub-1-Bit Compression of Trillion-Parameter Models.

FLAME: Towards Federated Fine-Tuning Large Language Models Through Adaptive SMoE QMoE: Practical Sub-1-Bit Compression of Trillion-Parameter Models

Reference 16

Resolution: unresolved; no resolver link, observed 2026-08-06T23:43:12.324753Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Pith citing papers

No inbound Pith citation observations are available.